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Record W7116900020 · doi:10.3138/seminar.61.4.2

“Die Geschichte unseres Landes ist so viel mehr als nur der Zweite Weltkrieg”: German Cultural History Meets Transnational Genre Narratives in <i>How to Sell Drugs Online (Fast)</i>

2025· article· en· W7116900020 on OpenAlexvenueno aff
Benjamin Schaper

Bibliographic record

VenueSeminar A Journal of Germanic Studies · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicGerman Literature and Culture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGermanNarrativeGerman historyAppealOrder (exchange)Cultural historyTelevision seriesGerman literature

Abstract

fetched live from OpenAlex

This article examines Netflix’s third original German series, How to Sell Drugs Online (Fast) (2019–), in order to situate German (streaming) television in the broader media developments of the convergence era. Transnationally conceived from the outset, the series combines transnational genre narratives with German cultural history in order to address broad audiences across the globe. Focusing on narrative complexity, intertextuality, and genre hybridity, the article first analyzes the series’ references to both national and international nerd narratives such as Baran bo Odar’s Who am I: Kein System ist sicher (2014) and David Fincher’s The Social Network (2010) . Then it contextualizes How to Sell Drugs within twenty-first-century societal debates in Germany and canonical works from nineteenth-century German literary tradition—especially Johann Wolfgang Goethe’s Die Leiden des jungen Werthers (1774) and Faust (1808) , as well as Frank Wedekind’s Frühlings Erwachen (1891) . In doing so, this article demonstrates that the series creates ambiguous images simultaneously inspired by both German and Anglo-American cultural history to appeal to audiences around the globe.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.302
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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